Hierarchical Modeling for Computational Biology

Carsten Maus, Mathias John, Mathias Röhl, Adelinde Uhrmacher

Formal Methods for Computational Systems Biology, pages 81-124
Lecture Notes in Computer Science 5016,  2008
Marco Bernardo, Pierpaolo Degano, Gianluigi Zavattaro (eds.)

Diverse hierarchies play a role in modeling and simulation for computational biology, e.g. categories, abstraction hierarchies, and composition hierarchies. Composition hierarchies seem a natural and straightforward focus for our exploration. What are model components and the requirements for a composite approach? How far do they support the quest for building blocks in computational biology? Modeling formalisms provide different means for composing a model. We will illuminate this with DEVS (Discrete event systems specification) and the pi calculus. Whereas in DEVS distinctions are emphasized, e.g. between a system and its environment, between properties attributed to a system and the system itself, these distinctions become fluent in the compact description of the pi calculus. However, both share the problem that in order to support a comfortable modeling, a series of extensions have been developed which also influence their possibility to support a hierarchical modeling. Thus, not individual formalisms but two families of formalisms and how they support a composite modeling will be presented. In computational biology one type of composite model deserves a closer inspection, as it brings together the wish to compose models and the need to describe a system at different levels in a unique manner, i.e. multi-level models.

Author = {Maus, Carsten and John, Mathias and R{\"o}hl, Mathias and Uhrmacher, Adelinde},
Booktitle = {Formal Methods for Computational Systems Biology},
Doi = {10.1007/978-3-540-68894-5_4},
Editor = {Bernardo, Marco and Degano, Pierpaolo and Zavattaro, Gianluigi},
Isbn = {978-3-540-68892-1},
Pages = {81--124},
Publisher = {Springer},
Series = {LNCS},
Title = {Hierarchical Modeling for Computational Biology},
Url = {http://www.springerlink.com/content/h0272g68824616hw/},
Url-Pdf = {http://www.springerlink.com/content/h0272g68824616hw/fulltext.pdf},
Volume = 5016,
Year = 2008
Partita IVA: 01131710376 - Copyright © 2008-2022 APICe@DISI Research Group - PRIVACY